ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (06/30/89)
The University of Waterloo
200 University Avenue
Waterloo, Ontario
The Institute of Computer Research (ICR)
Presents a Colloquium on
Organized C
by Mr. Jiri Soukup
of Code Farms, Inc., Richmond, Ontario
ABSTRACT
Organized C is a simple addition to C (or C ++) which allows automatic
management of data structures. From a theoretical point of view, Organized C
is a parametric type library of organizations with a convenient and efficient
interface. It forms the organizations in top-down fashion, as compared to
object-oriented languages based on classes that work essentially bottom-up.
Organized C is a spinoff from VLSI CAD, but is applicable to any general C
program. It is useful for complicated algorithms and for rapid development of
in-core databases which rely on a network of pointers.
After the presentation, there will be a demonstration for those interested.
Wednesday, July 5, 1989
3:30 p.m.
William G. Davis Computer Research Centre, Room 1302
Everyone is welcome. Refreshments served.ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (07/26/89)
The University of Waterloo
200 University Avenue
Waterloo, Ontario
The Institute of Computer Research (ICR)
Presents a Colloquium on
A Unified View of Propositional Knowledge Base Updates
by Hirofumi Katsuno
of NTT Basic Research Laboratories, Tokyo, Japan
ABSTRACT
The semantics of revising knowledge bases represented by sets of
propositional sentences is analyzed from a model-theoretic point of
view. The operation which incorporates new knowledge into knowledge
base is called revision. A characterization of all revision
schemes that satisfy the Gardenfors rationality postulates is
given in terms of an ordering among interpretations. A different kind
of change occurs when a sentence previously believed becomes
questionable; the operation that makes this change is called
contraction. Properties of the contraction operator that can be
defined in terms of revision are also studied. Two new update
operators, elimination and recovery, are introduced.
Elimination discards all previous preconceptions on a set of
propositional letters; recovery undoes the effect of the last update.
It is shown that elimination cannot be expressed as a contraction, and
that recovery is in general impossible. The existence of an invariant
part of the knowledge base comprising a set of integrity constraints
is considered and the definition of revision and contraction are
modified to take integrity constraints into account.
This is joint work with Alberto O. Mendelzon.
Wednesday, August 2, 1989
3:30 p.m.
William G. Davis Computer Research Centre, Room 1302
Everyone is welcome. Refreshments served.ksbooth@watcgl.waterloo.edu (Kelly Booth) (09/07/89)
Massively Parallel Processing for Graphics Dr. Frank Crow Principal Scientist Palo Alto Research Center Date: Wednesday, September 13, 1989 Time: 3:30 pm DC 1302 Place: Davis Centre, Room 1302 Abstract Many architectures and algorithms have been proposed for applying massively parallel methods to computer graphics. In recent years the onrush of technology has stampeded those of us who like to think about such things from the realms of fantasy and wishful thinking to the realm of the actually possible. A few massively parallel graphics systems have now actually been implemented. We can expect to see many more very soon. Can we really expect to attain, through parallel systems, the six orders of magnitude speedup necessary to produce today's most expensive imagery in real time? Answers may lie in looking at some current approaches to massive parallelism in graphics and the bottlenecks they leave. It will also help to look carefully at what is required to make images and how information must flow from shape descriptions to pixels. Refreshments The audience is invited to attend a wine & cheese reception at 4:30 pm in the ICR Lounge (DC 1301) immediately after the colloquium. This will be in lieu of the customary coffee and squares prior to the colloquium. A selection of wine, beer, and non-alcoholic beverages will be available, accompanied by fruit and cheese. The reception is hosted by the Institute for Computer Research, the Department of Computer Science, and the Computer Graphics Laboratory.
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (09/18/89)
ICR presents a colloquium on The Parallel Solution of Initial Value Problems For Ordinary Differential Equations, by Dr. Kenneth R. Jackson of the Computer Science Department, University of Toronto. Davis Centre, Room 1302 Wednesday Sept. 20, 1989 at 3:30 p.m. Usual refreshments will be served. . .
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (10/06/89)
ICR presents a colloquium on Abstraction in Artificial Intelligence Planning with Dr. Qiang Yang, Department of Computer Science, UW. Wednesday October 11, 1989 at 3:30. Davis Centre Room 1302 - refreshments will be served. Everyone welcome.
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (10/18/89)
ICR Colloquium Free-form Modeling with Implicit Quadratic Surfaces Wednesday, October 18, 1989 at 3:30 p.m. Davis Centre Room 1302 Dr. Joe Warren Department of Computer Science Rice University, Houston, Texas Everyone welcome. Refreshments will be served.
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (10/19/89)
ICR Colloquium A Practical Theory of Programming Dr. Eric C.R. Hehner Department of Computer Science University of Toronto Date: Wednesday, October 25, 1989 Time: 3:30 p.m. Place: Davis Centre Room 1302 ABSTRACT The logic of programs that we present is both simpler and more general than its competitors. In place of a pair of predicates (precondition and post-condition) as in Hoare Logic, or a function from predicates to predicates as in Dijkstra's predicate transformers, we offer a single predicate to serve as specification and as semantics. We do note require a Kleene squence or a least-fixed-point construction or any induction that is specific to programs or computation. We include time complexity. The logic covers sequential and parallel programming communcating processes and nonterminating computations. Everyone welcome. Refreshments served.
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (10/27/89)
ICR Colloquium HIgh Level Synthesis of Digital Hardware Dr. Raul Camposano IBM Thomas J. Watson Research Centre Date: Wednesday, November 1, 1989 Time: 3:30 p.m. Place: Davis Centre, Room 1302 Abstract High level synthesis is the automatic design of a register-transfer level structure that realizes a formally specified behaviour. This lecture gives an overview of the different issues involved in high-level synthesis , i.e., design representation, high-level optimizations, scheduling, allocation and interface to other design tools, mainly logic synthesis. It emphasizes the two central problems in high-level synthesis: scheduling and allocation. In synchronous designs, scheduling consists of assigning operations to discrete time slots called control steps. The hardware for the execution of the operations is defined during allocation. Scheduling and allocation are interrelated and depend on each other. The main algorithms for these transformations developed in Yorktown are shown. Finally some open problems such as design verification, design with constraints and pipeline synthesis are addressed. Coffee and cookies will be served. Everyone welcome.
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (11/04/89)
ICR Colloquium Inductive Reasoning and Kolmogorov Complexity Dr. Paul M.B. Vitanyi Centrum voor Wiskunde en Informatica The Netherlands & Universiteit van Amsterdam Faculteit Wiskunde en Informatica Date: Wednesday, November 8, 1989 3:30 p.m. Davis Centre, Room 1302 Abstract Reasoning to obtain the `truth about reality, from external data, is an important, controversial and complicated issue in man's effort to understand nature. Yet, today, we try to make machines do this. There have been old useful principles, new exciting models and intricate theories scattered in vastly different areas including philosophy of science, statistics, computer science and psychology. We focus on inductive reasoning in correspondence with the ideas of Solomonoff. While his proposal results in perfect procedures, they involve the noncomputable notion of Kolmogorov complexity. We develop the thesis that Solomonoff's method is fundamental in the sense that many other inductive principles can be viewed in particular ways to obtain comutable approximations of the method. We demonstrate this explicitly in the cases of Gold's paradigm for inductive inference, Valiant's learning (by adding computational requirements), Rissanen's principle and Jaynes' maximum entropy principle. We present several new theorems and derivations to this effect. We also delimit what can be learned and what cannot be learned in terms of Kolmogorov complexity and we describe an experiment, in machine learning of Kolmogorov complexity and its applications, now in progress. machine exerep
ylkingsbury@watdragon.waterloo.edu (Yvonne Kingsbury) (11/17/89)
The University of Waterloo
200 University Avenue
Waterloo, Ontario
The Institute of Computer Research (ICR)
Presents a Colloquium on
Using Spatial Coherence as a Local Teacher for a Neural Network
by Dr. Geoffrey Hinton
of Dept. of Computer Science and Psychology, University of Toronto
DATE: Wednesday, November 22, 1989
TIME: 3:30 p.m.
LOCATION: William G. Davis Computer Research Centre, Room 1302
ABSTRACT
A major goal of research on unsupervised learning
procedures is to discover an objective function that
defines the quality of an internal representation without
any externally supplied information about the desired
outputs of the system. If such a function could be found,
it should allow a hierarchy of representations to be
organized bottom-up in a time roughly linear in the depth
of the network. This would allow much faster learning than
supervised procedures which are generally very slow in
networks with many layers of hidden units. We propose that a
good objective for perceptual learning is to extract
higher-order features that are coherent across time or
space. This can be done by maximizing the explicit
mutual information between parameters extracted from
spatially or temporally adjacent parts of the input.
Recent results obtained by Sue Becker show that this kind
of objective function can be used to discover depth in
random-dot stereograms. The approach can be applied to
many other types of unsupervised perceptual learning. In
particular, it should be able to discover the underlying
three-dimensional shapes of objects when presented with
an ensemble of two-dimensional images.
Everyone is welcome. Refreshments served.rmvale@watcgl.waterloo.edu (Ruth Vale) (01/08/90)
ICR Colloquium Practical Applications of Interior Point Algorithms Dr. Anthony Vannelli Department of Electrical & Computer Engineering University of Waterloo Wednesday, January 10, 1990 at 3:30 p.m. Davis Centre 1302 Abstract Since the introduction of Narendra Karmarkar's polynomial time algorithm for solving linear programming problems in 1984, research in the mathematical optimization community has developed interior point variants to solve quadratic programming and combinatorial optimization problems. In this talk we outline our own research efforts to use an interior point algorithm to solve engineering- related optimization problems that arise in such diverse areas as water resource management, oil refinery multi-period planning problems and VLSI circuit layout problems. Our research on using a dual affine scaling interior point algorithm has led to promising resultsi in the outlined engineering areas. A developed and flexible algorithm is described for solving these large scale optimization problems. In particular the effective management of the key projection step which is the bottleneck step in any interior point code is described. We indicate how to exploit the structure of the underlying engineering design problem to minimize the difficulties caused by the projection step. Numerical results are described which show that our interior point algorithm is 5-20 times faster than the SIMPLEX code (MINOS) for solving these problems. Moreover, the algorithm becomes faster than the Simplex algorithm as the problem size increases. Everyone is welcome. Refreshments served.